FLAME-VQA: A Fuzzy Logic-Based Model for High Frame Rate Video Quality Assessment
Future Internet, 2023 In the quest to optimize user experience, network, and service, providers continually seek to deliver high-quality content tailored to individual preferences. However, predicting user perception of quality remains a challenging task, given the subjective
Štefica Mrvelj, Marko Matulin
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UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content [PDF]
IEEE Transactions on Image Processing, 2021 IEEE Transactions on Image Processing ...
Alan Bovik +2 more
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SB-VQA: A Stack-Based Video Quality Assessment Framework for Video Enhancement
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023 In recent years, several video quality assessment (VQA) methods have been developed, achieving high performance. However, these methods were not specifically trained for enhanced videos, which limits their ability to predict video quality accurately based on human subjective perception.
Ding-Jiun Huang +5 more
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Zoom-VQA: Patches, Frames and Clips Integration for Video Quality Assessment
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023 Accepted by CVPR 2023 ...
Kun Yuan
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Blind Video Quality Assessment for Ultra-High-Definition Video Based on Super-Resolution and Deep Reinforcement Learning [PDF]
Sensors, 2023 Ultra-high-definition (UHD) video has brought new challenges to objective video quality assessment (VQA) due to its high resolution and high frame rate.
Zefeng Ying, Da Pan, Ping Shi
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FAST-VQA: Efficient End-to-End Video Quality Assessment with Fragment Sampling
Lecture Notes in Computer Science, 2022 Current deep video quality assessment (VQA) methods are usually with high computational costs when evaluating high-resolution videos. This cost hinders them from learning better video-quality-related representations via end-to-end training. Existing approaches typically consider naive sampling to reduce the computational cost, such as resizing and ...
Wenxiu Sun, Chaofeng Chen, Weisi Lin
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Video quality prediction and classification using XGBoost under variable encoding and network conditions [PDF]
Scientific ReportsThis study presents a machine learning-based framework for video quality assessment (VQA). This framework enables the mapping of objective metric outputs, such as Structural Similarity Index Measure (SSIM) and Video Multimethod Assessment Fusion (VMAF ...
Jaroslav Frnda +4 more
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LMM-VQA: Advancing Video Quality Assessment With Large Multimodal Models
IEEE Transactions on Circuits and Systems for Video TechnologyThe explosive growth of videos on streaming media platforms has underscored the urgent need for effective video quality assessment (VQA) algorithms to monitor and perceptually optimize the quality of streaming videos. However, VQA remains an extremely challenging task due to the diverse video content and the complex spatial and temporal distortions ...
Xiongkuo Min, Guangtao Zhai
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Towards Quality Assessment for Arbitrary Translational 6DoF Video: Subjective Quality Database and Objective Assessment Metric [PDF]
EntropyArbitrary translational Six Degrees of Freedom (6DoF) video represents a transitional stage towards immersive terminal videos, allowing users to freely switch viewpoints for a 3D scene experience. However, the increased freedom of movement introduces new
Chongchong Jin, Yeyao Chen
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Realistic benchmark RBD360 dataset for quality assessment of random user generated 360° videos [PDF]
Scientific ReportsUser-generated 360° video content is becoming increasingly popular due to the availability of low-cost acquisition devices and its inherently immersive nature.
Manav Arun Mehta +5 more
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